tbuckley/cabot-search huggingface dataset:
Navigator utilization rates in breast cancer patients by race in a comprehensive cancer center.
Authors: Louisa Onyewadume, Ursula Burnette, Chesley Cheatham, Shearwood McClelland
Journal: Journal of Clinical Oncology (2023)

e18501 Background: African-Americans have the highest overall cancer death rate and shortest survival time of any racial or ethnic group in the United States. Elucidation of disparities in cancer care access is important since previous work has indicated that when equal access to Radiation Therapy (RT) in prospective randomized trials is granted, race does not independently affect outcomes. The most common cancer studied in African-American radiation therapy (RT) access disparities research is breast cancer. Furthermore, prospective analyses have demonstrated that African-Americans receive hypofractionation following breast-conserving surgery less frequently than Caucasians. As such, the goal of this study is to eventually evaluate the impact of patient navigation on short-course RT access for African-American breast cancer patients. Methods: Our study is a prospective survey-based evaluation of the impact of patient navigation on access to hypo-fractionated RT and financial toxicity in African-American breast cancer patients. As the first step to investigating the impact of patient navigation on RT access in this population, medical records of women with breast cancer in our center (University Hospitals Cleveland Medical Center, Seidman Cancer Center) were identified from support groups. The baseline navigation rate for this population was determined from the initial data collected during tumor board sessions from June 2022 through October 2022. Results: We identified female patients who were diagnosed with breast cancer and thus were eligible for navigation. From June 1 st through October 31 st , 30 female patients were identified. Nine (30%) were Caucasian and 21 (70%) were African-American. Of the 21 African-American female patients, only four (19%) were connected with patient navigation services. Of the 9 Caucasian female patients, only four (44.4%) were connected with patient navigation services; this difference between African-American and Caucasian patients did not reach statistical significance. The total baseline navigation rate at our center during this period was 26.67% (8 out of 30 patients). Conclusions: Over a recent five-month period, it was determined that the baseline navigation rate for Caucasian female breast cancer patients is numerically more than 2x that of African-American female patients at our comprehensive cancer center. This information is an important precursor to the first investigation of the impact of patient navigation on reducing RT access disparities facing African-American breast cancer patients. We anticipate that after collating and analyzing survey results for patients pre-RT versus post-RT as well as for those with versus without patient navigation, navigation will serve to overcome barriers in compliance to therapy and increase adherence to optimal care.
Multicenter, retrospective population-based study on the incidence of medication-related osteonecrosis of the jaw in patients with breast cancer with bone metastases.
Authors: Christine Brunner, Christian Marth, Daniel Egle, Magdalena Ritter, Florentina Baumgart, Miriam Elisabeth Emmelheinz, Benjamin Walch, Claudia Iannetti, August Zabernigg, Maria Castellan, Oliver Tibor Andraschofsky, Alice Markl, Michael Hubalek, Michael Schnallinger, Ewald Woell, Sibylle Puntscher, Marjan Arvandi, Uwe Siebert, Emanuel Bruckmoser, Johannes Laimer
Journal: Journal of Clinical Oncology (2023)

6588 Background: Antiresorptive therapy with bisphosphonates or denosumab is standard care for patients with primary or secondary osseous metastasized breast cancer. The most important toxicity of this class of drugs is medication-related osteonecrosis of the jaw (MRONJ). MRONJ represents a major medical burden and impairs quality of life. Based on recent studies, the risk of MRONJ occurrence ranges from 1% to 3%. The objective of this study was to assess the population-based incidence of MRONJ in breast cancer patients with bone metastases in Tyrol, Austria. Methods: This retrospective multicenter study was conducted between 2000 and 2020 at nine centers across Tyrol, Austria, including 8,860 patients with breast cancer. Depending on whether patients with bone metastases received denosumab, bisphosphonates or denosumab following bisphosphonates they were allocated to one of three groups. Data was collected using an electronic case report form (e-CRF) and managed via the web-based database AskiMed. MRONJ incidences with 95% confidence intervals and the differences between the median of cumulative incidences were calculated in patients treated with bisphosphonates and/or denosumab. Results: A total of 639 patients had bone metastasis and received antiresorptive therapy. MRONJ was diagnosed in 56 (8.8%) patients. Regarding the 292 (45.7%) patients treated with denosumab alone, the MRONJ incidence was 11.6% (95%CI 8.2%-15.9%). The group of patients treated with only bisphosphonates included 255 (39.9%) patients; their MRONJ incidence was 2.7% (95%CI 1.1%-5.6%). Of the 92 (14.4%) patients receiving both antiresorptive therapies consecutively, the MRONJ incidence was 16.3% (95%CI 9.4%-25.5%). Thus, a total of 49 (12.8%) MRONJ cases were detected in patients using denosumab alone as well as using the combination of denosumab following bisphosphonates. Patients treated with denosumab developed a MRONJ in median 60 months earlier than with bisphosphonates alone or followed by denosumab. The hazard ratio for MRONJ from start of therapy of denosumab compared to bisphosphonates alone or followed by denosumab was 7.9 (3.8-16.2; p-value &lt; 0.0001). Conclusions: This study showed a substantially higher MRONJ incidence for denosumab alone or bisphosphonates followed by denosumab in the tyrolean cohort when compared to other recent studies. Future comparative real-world-evidence research provide explicit benefit-harm tradeoffs to inform treatment decision making.
Real-world analysis of cardiac, gastrointestinal, and hematologic toxicities between commonly used antiemetics in everyday oncology clinical practice.
Authors: Kavitha Beedupalli, Anil Ananthaneni, Dawood Findakly
Journal: Journal of Clinical Oncology (2023)

6587 Background: Antiemetics are highly effective in chemotherapy-induced nausea and vomiting. We utilized Food and Drug Administration Adverse Event Reporting System (FAERS) database to evaluate adverse events (AEs) caused by selected antiemetics commonly used in outpatient oncology practice. Methods: We analyzed the FAERS database to assess the cardiac, gastrointestinal (GI), and hematologic AEs for metoclopramide, olanzapine, ondansetron, and promethazine from 2013 through 2022. The disproportionality signal was analyzed by calculating Reporting Odds Ratio (ROR) with a 95% confidence interval (CI)—considered significant when the lower limit of 95% CI was &gt; 1. Results: A total of 20,302 AEs were identified, out of which 8,135 (40.1%) were cardiac—arrhythmia and QTc prolongation; 8,656 (42.5%) were GI—nausea/vomiting, constipation/diarrhea, abdominal pain/discomfort, and dyspepsia; and 3,511 (17.3%) were hematologic—leukopenia, thrombocytopenia, anemia, and pancytopenia. Compared to other antiemetics, promethazine and olanzapine had higher cardiac and hematologic AEs, respectively, whereas metoclopramide, followed by ondansetron had higher GI AEs (Table). Conclusions: Antiemetics are readily available and effective, yet the preference for a particular drug or drug combination varies. Our study highlights selected antiemetics AEs in order to help individualize treatment for this often challenging and frequently encountered entity. [Table: see text]
Study of endometrial carcinoma on correlation between molecular typing and lymph node metastasis and construction of prediction model.
Authors: Quanhong Jiang, Qiuyue Han, Kun Song, Ran Chu, Yong Zhao, Zhaoyang Zhang, Zhuang Li
Journal: Journal of Clinical Oncology (2023)

e17621 Background: TCGA molecular typing was proposed by The Cancer Genome Atlas (TCGA) in 2013 and recommended by the fifth edition of WHO, which has a strong prognositic value and is included in the risk stratification system, clinical diagnosis and treatment decision-making system of endometrial cancer (EC) patients. Meanwhile, Lymph node management in patients with EC is still controversial. Lymph node dissection (LND) and sentinel lymph node biopsy (SLNB) have their own advantages and limitations. This study attempts to establish a predictive model for lymph node metastasis (LNM) in patients with EC based on molecular typing and other clinical features and establish risk stratification, in order to provide a feasible method for predicting LNM in EC. Methods: In this study, SPSS19, R 4.2.1 and python 3.6 were used to establish a nomogram and evaluate it through a number of indicators, and the model was repeatedly verified by machine learning algorithms. With LNM as the outcome, risk stratification was set through the cut-off value of nomogram score to guide clinical treatment. Finally, an online LNM prediction website was designed to help patients. Results: A total of 325 EC patients were included, 35 (10.8%) with LNM and 290 (89.2%) without LNM. CA125 and cervical involvement were significantly correlated with LNM (p &lt; 0.001), molecular typing, neutrophil to lymphocyte ratio (NLR), menstrual status were associated with LNM (p &lt; 0.05). Lasso analysis screened out four independent factors: molecular typing, CA125, cervical involvement and menstrual status. The nomogram model was established by logistics regression (LR), with the prediction accuracy of the training set and validation set of 0.890 and 0.886, respectively. Machine learning algorithms in the training set also validates the model. Meanwhile, a risk stratification is established by the cut-off value of nomogram. We define high-risk group of LNM with more than the cut-off value and LND is recommended, while below the value is low-risk group and SLNB is recommended. Conclusions: We have established a nomogram clinical prediction model incorporating four factors, practicing stratified medical treatment about LND and SLNB, and formed a website for LNM prediction, genuinely providing patients recommendations.
Ultra-sensitive baseline-informed MRD assay to predict prognosis outcomes in patients with resectable hepatocellular carcinoma.
Authors: Jie Hu, Haoran Tang, Feng Xie, Yue Zhang, Shidong Jia, Jian Zhou
Journal: Journal of Clinical Oncology (2023)

e16228 Background: The detection of minimal residual disease (MRD) has been shown to be a potential biomarker for the prognosis and post-surgery treatment of resectable hepatocellular carcinoma (HCC). However, the application of MRD in HCC has been limited by the traditional requirement of carrying out MRD over 30 days post-surgery, which is often incompatible with the time window for adjuvant treatment decisions. Additionally, MRD results may be impacted by post-surgery imbalances if assayed too soon after surgery. Methods: This retrospective study enrolled 255 early-stage HCC patients who received surgical resections and had complete information on relapse and survival. Matched tumor and normal tissue samples were collected at the time of surgery and plasma samples were collected as early as 7 days post-surgery. An ultra-sensitive, baseline-informed MRD assay (PredicineBEACON) was used to evaluate the correlation between peri-surgical MRD status and prognosis outcomes. Somatic mutations were identified through PredicineWES+ whole exon sequencing, and up to 50 somatic mutations were selected for the design of a patient-specific capture panel, in addition to a fixed panel of 500 actionable variants. Results: The study has completed MRD tests for 58 patients, of which 8 were called MRD positive with ≥0.005% tumor fractions. The tumor fraction proportion of MRD-positive patients ranged from 0.008% to 5.653% (median 0.315%). The relapse-free survival (RFS) and overall survival (OS) were correlated with MRD status: the median RFS of MRD-positive patients was 13.9 months compared to not reached after 44.4 months for MRD-negative patients (p = 0.1), and the median OS of MRD-positive patients was 27.2 months compared to not reached after 55.5 months for MRD-negative patients (p = 0.03). Conclusions: Our results demonstrate the feasibility of using an ultra-sensitive, baseline-informed MRD assay to detect strong correlations between MRD status and prognosis outcomes in peri-surgical plasma samples collected as early as 7 days post-surgery in resectable HCC patients. This study highlights the clinical utility of MRD testing in peri-surgical settings.
Quality dashboards: Uncovering potential health disparities.
Authors: Kevin Juan Zhang, Aya Sato-DiLorenzo, Melis Celmen, Rosemary Chude-Sokei, Tenzin Dechen, Ashley L. O’Donoghue, Jessica Ann Zerillo
Journal: Journal of Clinical Oncology (2023)

e18567 Background: A number of demographic characteristics and social determinants of health have been demonstrated to impact cancer outcomes. It is essential to assess quality metrics stratified by these characteristics so that potential disparities may be identified and addressed amongst marginalized populations. Methods: We examined our Cancer Center’s quality dashboard’s quality metrics and identified which could be stratified by race, ethnicity, language preference, sexual identity, and gender. Databases included Vizient, Press Ganey, Tumor Registry, and our institution’s performance reports. Where data was available, we conducted cross-group comparisons to assess for differences in outcomes. ANOVA and Fisher’s exact tests were performed to compare groups. A P-value of &lt; 0.05 was considered statistically significant. Results: Of the 13 metrics, six (46%) could be stratified by demographic characteristics (likelihood to recommend the practice, mortality index, length of stay index, 30-day readmission, return to the operating room, adequate lymph node sampling). Six (46%) could not be stratified due to a lack of demographic information (new patient access, medication harm events, distress screening, preventable admissions, preventable emergency department visits, survivorship care plan). One metric was not at the patient-level, and thus did not apply to our investigation (non-template chemotherapy orders). More White patients (86.1%) were very likely to recommend the practice compared to Black (72.1%) or Asian patients (60.1%) (P &lt; 0.001). Additionally, significantly more English speakers were likely to recommend the practice than non-English speakers (84% vs. 65%; P &lt; 0.001). A significant difference was found in the 30-day readmission rate when stratified by race (White [8.2%] vs. Black [8.8%] vs. Asian [10.6%] vs. other [14.5%] vs. unknown [1.0%]; P = 0.02). No significant group differences were found in mortality index, length of stay, the proportion of adequate lymph node sampling, or returning to the operating room. Notably, the proportion of patients with “unknown” race and ethnicity ranging from 3.9%-17.5% for five metrics, represented the second largest group behind White race and non-Hispanic ethnicity. Conclusions: Less than half of the quality dashboard’s core metrics could be stratified by demographic characteristics. Even when data was available, the high frequency of missing data identifies a need for improved data collection accuracy so that more meaningful assessments can be made. Existing data suggests a disparity exists for patients of limited English proficiency having a lower satisfaction with the practice. This warrants further exploration in order to close gaps in cancer quality outcomes.
Clinical analysis of optimized neural network risk models to predict clinically significant prostate cancer and avoid unnecessary prostate biopsies.
Authors: Christopher J.D. Wallis, Robert J Paproski, Desmond Pink, Catalina Vasquez, Adrian S. Fairey, M Eric Hyndman, Armen G. Aprikian, Adam Kinnaird, Perrin Beatty, Christian P. Pavlovich, Leonard S. Marks, John D Lewis
Journal: Journal of Clinical Oncology (2023)

5023 Background: Given the low specificity of the current standard of care diagnostic tests for prostate cancer (PCa), there is an unmet clinical need for higher specificity tests to counter overdiagnosis of grade group (GG) 1 PCa. The aim of the study was to create optimized neural network risk models using PSA, free PSA, and other useful clinical features, and to validate the accuracy of the risk models to predict GG ≥2 PCa using real-world samples and data. Methods: Men aged 40-75 years with PSA &gt;=3ng/mL and a biopsy referral were recruited into cohorts from sites in Canada (Kipnes Urology Centre (KUC), Edmonton, AB, and Prostate Cancer Centre (PCC), Calgary, AB) and the United States (Johns Hopkins University (JHU), Baltimore, ML and UCLA, Los Angeles, CA). Risk models to predict all GGs or GG ≥2 PCa were fit using data from KUC and JHU (train cohort n = 1037) while fixed models were validated on PCC (n = 401) and UCLA (n = 945). Prediction models were created using neural networks to generate the patient’s risk score. To compare the risk model test with PSA, the high-grade cancer detection sensitivity was fixed, and the number of biopsies needed to achieve that sensitivity was evaluated. Threshold values for the training cohort were determined using at least 95% sensitivity and maximum specificity. Threshold values for other clinical features and risk calculator outputs were set to match the test sensitivity when possible. Results: The optimized neural network risk models test had the highest area under the curve (AUC 0.81) for predicting GG ≥2 PCa on the validation cohorts compared to four other risk calculators; Prostate Cancer Prevention Trial Risk Calculator 2.0 (PCPTRC) with free PSA (0.78, p-value&lt;0.001), Prostate Biopsy Collaborative Group risk calculator (PBCG, 0.73, p-value&lt;0.0001), European Randomized study of Screening for Prostate Cancer risk calculator 3 (ERSPC-3, 0.72, p-value&lt;0.0001), and PCPTRC with no free PSA (0.71, p-value&lt;0.0001) and PSA (0.66, p-value&lt;0.0001). At a threshold of 18.6%, this test provided 94% sensitivity, 37% specificity, 49% positive predictive value, and 90% NPV for predicting GG ≥2 PCa. If a biopsy was performed only when the tests’ risk score prediction was ≥17.8% for GG ≥2 PCa, 36-44% of unnecessary prostate biopsies could be avoided while missing 4-12% of patients with GG ≥2 prostate cancer. Conclusions: This neural network risk model is a tool that can be used to inform the physician of a patient’s risk of having GG ≥2 PCa on prostate biopsy. Using this novel test in the clinic is expected to significantly reduce the number and burden of unnecessary prostate biopsies. [Table: see text]
Impact of a pathologist-driven molecular testing protocol on veterans with non-small cell lung cancer.
Authors: Rui Li, M. Carmen Frias Kletecka, Daniel Sanghoon Shin
Journal: Journal of Clinical Oncology (2023)

e21209 Background: Precision medicine has shifted the paradigm of cancer treatment in the last two decades. Currently, with over ten targetable mutations in non-small cell lung cancer (NSCLC) and increasingly emerging biomarkers for immunotherapy, genomic testing is necessary for every NSCLC patient. However, this multiple biomarker-defined treatment approach is often compromised by many challenges including slow turnaround time (TAT), high rate of quantity not sufficient (QNS) resulting in inaccurate molecular testing or needs for second biopsy. These barriers lead to increased risk of developing medical complications from re-biopsy or treatment delay as well as additional social and financial support, which is not always available for veterans. A recent study reported that up a one third of veterans with NSCLC containing highly actionable mutations were not prescribed targeted treatment, among which, 25% of patients do not have a documented molecular testing results. Herein, we reported a pathologist-driven protocol to enhance the implement of molecular testing on guiding NSCLC treatment in veteran population. Methods: A pathologist-driven molecular testing protocol is applied West Los Angeles VA hospital since 2018. First, in preparation for diagnosis and molecular testing, tissue block will be cut in serial sections in the following priority: 2 slides for H&amp;E, 4 slides for IHC, 2 slides for PD-L1 staining. An additional slide is made for quality control (QC) purpose before 10 additional slides are cut for molecular testing and 6 for FISH studies. The reminder of the tissue block will be cut in serial sections and preserved in a vial along with tissue shaved at initial block effacement. Every tissue block will be exhausted. Upon initial evaluation of H&amp;E slides, the reviewing pathologist, independent of the treating oncologist, will order molecular testing including EGFR, ALK, ROS and BRAF by NGS if NSCLC is identified. PD-L1 IHC staining is also ordered automatically regardless of the histology. If a clinically actionable mutation is detected, a mutation notification is immediately sent via email by the molecular pathologist to alert the treating oncologist. Results: After implementing this protocol, we observed a decreased rate of QNS (~30% reduction) and subsequently the need for 2 nd biopsy dropped substantially. We also observed a faster TAT between initial cancer diagnosis (within 7 days) and the resulting of molecular testing to guide subsequent treatment. Conclusions: Refined tissue processing and pathologist driven ordering system can significantly impact initial management of patients with NSCLC as it reduces the rate of QNS and repeat biopsy/TAT. This protocol can be easily implemented in VA system or other community based healthcare system.